// Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
//     http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.

#pragma once

#include "paddle/phi/core/dense_tensor.h"
#include "paddle/phi/infermeta/binary.h"

namespace phi {

template <typename T, typename Context>
void DivideKernel(const Context& dev_ctx,
                  const DenseTensor& x,
                  const DenseTensor& y,
                  DenseTensor* out);

template <typename T, typename Context>
void Divide(const Context& dev_ctx,
            const DenseTensor& x,
            const DenseTensor& y,
            DenseTensor* dense_out) {
  MetaTensor meta_out(dense_out);
  ElementwiseInferMeta(x, y, &meta_out);
  if (x.initialized()) {
    DivideKernel<T, Context>(dev_ctx, x, y, dense_out);
  }
}

template <typename T, typename Context>
DenseTensor Divide(const Context& dev_ctx,
                   const DenseTensor& x,
                   const DenseTensor& y) {
  DenseTensor dense_out;
  Divide<T, Context>(dev_ctx, x, y, &dense_out);
  return dense_out;
}

}  // namespace phi
